PROJECT SUMMARY Mycobacterium tuberculosis (Mtb) caused 1.3 million global deaths in 2017, yet an effective vaccine remains elusive. A major challenge in the field has been selecting which Mtb antigens (from among >4000 proteins) to include in a vaccine, and what T cell functions it should aim to elicit. Previous attempts to define protective immunity against Mtb have shown mixed success and have focused on diversity in one dimension at a time ? eg using proteins / lyates to identify diverse CD4 T cell states (eg cytokine polyfunctionality), or defining cytokine production in response to diverse peptides predicted to bind human leukocyte antigens (HLAs). We hypothesize that deep, simultaneous analysis of both T cell specificity and phenotype will: (i) reveal an interdependence between these 2 dimensions of the anti-Mtb response that is not currently well-understood, and (ii) enable, in future studies, improved correlates of protection against disease that can empower vaccine studies and inform treatment strategies. To achieve this new `deep-2D' view of the response, we propose to integrate 2 novel technologies: (i) a platform we recently developed for experimentally screening the Mtb proteome for peptides that bind diverse HLA class II proteins (`PepSeq'), and (ii) single cell sequencing, enabling linked analysis of transcriptome and peptide:HLA binding within thousands of T cells. If successful, this project would establish a rationale and toolkit for `deep-2D' analysis of the T cell response to Mtb that we could subsequently apply to larger cohorts designed to reveal correlates of disease protection in both natural history and vaccine settings. The approach would also be directly applicable to other complex pathogens.